Timeline for Transpose of a very large matrix with fewer than 1021 rows with Python
Current License: CC BY-SA 4.0
7 events
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| Mar 19, 2019 at 17:34 | history | edited | Alex Reynolds | CC BY-SA 4.0 |
added 48 characters in body
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| Mar 19, 2019 at 17:31 | vote | accept | Alex Reynolds | ||
| Mar 19, 2019 at 16:04 | comment | added | Alex Reynolds |
Unfortunately, I can't read the file into memory, otherwise I'd use datamash or awk if I could. The mmap approach looks interesting, thanks!
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| Mar 19, 2019 at 11:44 | comment | added | Toby Speight |
Have you considered mmap and offsets as an alternative to file descriptors? That might be easier to work with. It certainly scales to more rows.
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| Mar 19, 2019 at 11:39 | comment | added | Graipher | While you did say how many rows your matrix has, you did not specify the number of columns. If that is less than a million or so, reading it all into memory and transposing it there will be faster. | |
| Mar 19, 2019 at 11:30 | answer | added | Oh My Goodness | timeline score: 5 | |
| Mar 19, 2019 at 9:32 | history | asked | Alex Reynolds | CC BY-SA 4.0 |